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==Forsooth==
==Forsooth==
----
"There are 33 percent more such women in their 20s than men. To help us see what a big difference 33 percent is,
Birger invites us to imagine a late-night dorm room hangout that’s drawing to an end, and everyone wants to hook up.
'Now imagine,' he writes, that in this dorm room, 'there are three women and two men.'"


<div align=right>--from the ''New York Times Book Review''</div>
==Quotations==
Cited in [https://quomodocumque.wordpress.com/2015/11/20/imagine-33-percent/ Imagine 33 percent] at Jordan Ellenberg's "Quodmodocumque" blog (20 November 2015).
“We know that people tend to overestimate the frequency of well-publicized, spectacular
 
events compared with more commonplace ones; this is a well-understood phenomenon in
Submitted by Priscilla Bremser
the literature of risk assessment and leads to the truism that when statistics plays folklore,
folklore always wins in a rout.”
<div align=right>-- Donald Kennedy (former president of Stanford University), ''Academic Duty'', Harvard University Press, 1997, p.17</div>


----
----
“I showed all the data together, which helped disguise the bimodal distribution. Nothing wrong with that.
All the data is there. Every piece.... [But then he suggested using] thick and thin lines to try and dress it up,
or changing colors to divert attention.”


<div align=right>--Bob Schubert (Takata airbag engineer)</div>
"Using scientific language and measurement doesn’t prevent a researcher from conducting flawed experiments and drawing wrong conclusions — especially when they confirm preconceptions."


quoted in: [http://www.nytimes.com/2016/01/05/business/takata-emails-show-brash-exchanges-about-data-tampering.html Takata emails show brash exchanges about data tampering], ''New York Times'', 4 January 2016
<div align=right>-- Blaise Agüera y Arcas, Margaret Mitchell and Alexander Todoorov, quoted in: The racist history behind facial recognition, ''New York Times'', 10 July 2019</div>


Submitted by Bill Peterson
==In progress==
[https://www.nytimes.com/2018/11/07/magazine/placebo-effect-medicine.html What if the Placebo Effect Isn’t a Trick?]<br>
by Gary Greenberg, ''New York Times Magazine'', 7 November 2018


==cancer prevention==
[https://www.nytimes.com/2019/07/17/opinion/pretrial-ai.html The Problems With Risk Assessment Tools]<br>
[http://www.nytimes.com/2016/07/06/upshot/helpless-to-prevent-cancer-actually-a-lot-is-in-your-control.html Helpless to prevent cancer? Actually, quite a bit Is in your control]<br>
by Chelsea Barabas, Karthik Dinakar and Colin Doyle, ''New York Times'', 17 July 2019
By Aooron E. Carroll, TheUpshot blog, ''New York Times'', 5 July 2016
==Explaining==
[http://magazine.amstat.org/blog/2016/07/01/prescorner-jul16/ We Have Some Serious Explaining to Do]
<br>
by Rob Santos, AMSTAT News, 1 July 2106


==Conflicting polls==
==Hurricane Maria deaths==
Jeff Witmer sent the following to the Isolated Statisticians list:
Laura Kapitula sent the following to the Isolated Statisticians e-mail list:


:[http://www.nytimes.com/2016/07/18/upshot/confused-by-contradictory-polls-take-a-step-back.html?_r=0 Confused by contradictory polls? Take a step back]<br>
:[Why counting casualties after a hurricane is so hard]<br>
:by Nate Cohn, "Upshot" blog, ''New York Times'', 18 July 2016
:by Jo Craven McGinty, Wall Street Journal, 7 September 2018


==Algorithms aren't objective==
The article is subtitled: Indirect deaths—such as those caused by gaps in medication—can occur months after a storm, complicating tallies
Laura noted that
:[https://www.washingtonpost.com/news/fact-checker/wp/2018/06/02/did-4645-people-die-in-hurricane-maria-nope/?utm_term=.0a5e6e48bf11 Did 4,645 people die in Hurricane Maria? Nope.]<br>
:by Glenn Kessler, ''Washington Post'', 1 June 2018


Jo Hardin sent to the Isolated Statiticians.
The source of the 4645 figure is a [https://www.nejm.org/doi/full/10.1056/NEJMsa1803972 NEJM article].  Point estimate, the 95% confidence interval ran from 793 to 8498.


[https://www.patreon.com/posts/episode-17-high-5748681 Not So Standard Deviations]
President Trump has asserted that the actual number is
[https://twitter.com/realDonaldTrump/status/1040217897703026689 6 to 18].
The ''Post'' article notes that Puerto Rican official had asked researchers at George Washington University to do an estimate of the death toll.  That work is not complete.
[https://prstudy.publichealth.gwu.edu/ George Washington University study]


==Ice cream and IQ==
:[https://fivethirtyeight.com/features/we-still-dont-know-how-many-people-died-because-of-katrina/?ex_cid=538twitter We sttill don’t know how many people died because of Katrina]<br>
[http://www.economist.com/blogs/graphicdetail/2016/04/daily-chart Daily Chart:  Ice Cream and IQ]<br>
:by Carl Bialik, FiveThirtyEight, 26 August 2015
''The Economist'', 1 April 2016


The [http://www.snopes.com/wordpress/wp-content/uploads/2016/04/20160402_WOC883.png chart] shows per capita ice cream consumption for a sample of countries plotted against mean scores on a standardized reading test. A positive association (R^2 = 0.49) is demonstrated.
----
[https://www.nytimes.com/2018/09/11/climate/hurricane-evacuation-path-forecasts.html These 3 Hurricane Misconceptions Can Be Dangerous. Scientists Want to Clear Them Up.]<br>
[https://journals.ametsoc.org/doi/abs/10.1175/BAMS-88-5-651 Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane Season]<br>
[https://www.nhc.noaa.gov/aboutcone.shtml Definition of the NHC Track Forecast Cone]
----
[https://www.popsci.com/moderate-drinking-benefits-risks Remember when a glass of wine a day was good for you? Here's why that changed.]
''Popular Science'', 10 September 2018
----
[https://www.economist.com/united-states/2018/08/30/googling-the-news Googling the news]<br>
''Economist'', 1 September 2018


Note the date!
[https://www.cnbc.com/2018/09/17/google-tests-changes-to-its-search-algorithm-how-search-works.html We sat in on an internal Google meeting where they talked about changing the search algorithm — here's what we learned]
----
[http://www.wyso.org/post/stats-stories-reading-writing-and-risk-literacy Reading , Writing and Risk Literacy]


==Concussions==
[http://www.riskliteracy.org/]
[http://www.nytimes.com/2016/03/25/sports/football/nfl-concussion-research-tobacco.html In N.F.L., Deeply Flawed Concussion Research and Ties to Big Tobacco]<br>
-----
By ALAN SCHWARZ, WALT BOGDANICH and JACQUELINE WILLIAM SMARCH 24, 2016
[https://twitter.com/i/moments/1025000711539572737?cn=ZmxleGlibGVfcmVjc18y&refsrc=email Today is the deadliest day of the year for car wrecks in the U.S.]
Continue reading the main storyShare This Page
 
 
==Tests for gerrymandering==
[http://www.nytimes.com/2015/12/06/opinion/sunday/let-math-save-our-democracy.html Let math save our democracy]<br>
by Sam Wang, ''New York Times'', 5 December 2015
 
[http://www.washingtonpost.com/wp-srv/special/politics/gerrymandering/ How gerrymandered is your Congressional district?]<br>
by Christopher Ingraham, ''Washington Post'',15 May 2014
 
appeal to [https://en.wikipedia.org/wiki/Isoperimetric_inequality isoperimetric inequality]: in the plane, a circle maximizes the area of a closed curve with a fixed perimeter.
 
[http://www.economist.com/node/1099030 How to rig an election]<br>
''Economist'', 25 April 2002
 
Subtitled: "In a normal democracy, voters choose their representatives. In America, it is rapidly becoming the other way around."
 
"Worst of all is the state's extraordinary 17th District, which is a crab (see chart). Though most of it lies in the western part of the state, two claws stretch out towards the eastern part to grab Democratic cities in order to make the surrounding 18th and 19th districts more reliably Republican."
 
"as used to be said of the old Texas 6th (which was a road from Houston to Dallas), that you could kill most of the constituents by driving down the road with the car doors open."
 
==Diet science==
[http://www.nytimes.com/2015/10/13/upshot/are-fats-unhealthy-the-battle-over-dietary-guidelines.html Are fats unhealthy? The battle over dietary guidelines]<br>
by Aaron E. Carroll, “Upshot” blog,  ''New York Time''s, 12 October 2015.
 
Related “Upshot”:  [http://www.nytimes.com/2015/02/24/upshot/behind-new-dietary-guidelines-better-science.html Behind new dietary guidelines, better science],  February 23, 2015
 
==Chance of gun death==
http://www.nytimes.com/2015/12/05/upshot/in-other-countries-youre-as-likely-to-be-killed-by-a-falling-object-as-a-gun.html?rref=upshot&module=Ribbon&version=context&region=Header&action=click&contentCollection=The%20Upshot&pgtype=Multimedia
 
 
==Earthquake prediction==
[http://www.latimes.com/science/la-me-quake-prediction-20151023-story.html Why a 99.9% earthquake prediction is 100% controversial]<br>
by Rong-Gong Lin II, ''Los Angeles Times'', 23 October 2015
 
"This [http://geodesy.unr.edu/publications/DonnellanEtAl2015.pdf report]
<blockquote>
Donnellan added that the USGS' 85% probability and her 99.9% chance still favored a big earthquake in the next three years. 
 
"If an earthquake happens in three years, we're both right," Donnellan said.
</blockquote>
 
USGS https://www.facebook.com/USGeologicalSurvey/posts/955479124498071:0 responded]
 
==Simulating the lottery==
[http://graphics.latimes.com/powerball-simulator/ Here’s $100. Can you win $1.5 billion at Powerball?]<br>
by Jan Schleuss, ''Los Angeles Times'', 8 January 2016 (updated 12 Jan 2016)
 
By Wednesday January 13 of this year, the Powerball jackpot had reached $1.6 billion, making it the [https://en.wikipedia.org/wiki/Lottery_jackpot_records largest lottery jackpot in history].  There were three winners that day.  This article, published the week before as the prize was still growing, was one of many examples in the popular press intended to inform people how remote the chance of winning (1 in 292,201,338 ) really was.  It includes an online tool that allows the user to select their lucky numbers, and then observe their fate over the course of 50 simulated drawings, which is $100 worth of plays.  Here's the message I got after one try.  No jackpot, but my minor prizes were automatically invested in more tickets.
 
<blockquote>You've played the lottery 54 times over about 6 months and spent $108, but won $8. You're in the hole $100.  So why not throw some more money at that problem? [The options offered are to bet $100, $1000, or your whole paycheck.]
</blockquote>
 
By contrast, the ''New York Times'' tried to explain the hopelessness in prose [http://www.nytimes.com/2016/01/13/us/powerball-odds.html] (NYT, 12 January 2016).  The article lists some time-honored comparisons: the 1 in 1.19 million chance that a US resident will be  [http://www.lightningsafety.noaa.gov/odds.shtml hit by lightning in a year] and the 1 in 12,500 chance that an amateur golfer will [http://www.golfdigest.com/story/want-to-know-your-odds-for-a-hole-in-one-well-here-they-are make a hole-in-one].
 
For a fresher perspective, see Ron Wasserstein's excellent piece  [http://www.huffingtonpost.com/ronald-l-wasserstein/chances-of-winning-powerball-lottery_b_3288129.html A statistician’s view: What are your chances of winning the Powerball lottery?] (thisoriginally appeared in the ''Huffington Post'' on 16 May 2013, and was updated 7 January 2016).
 
===Followup===
[http://www.bostonglobe.com/metro/2016/01/13/copycats-more-than-half-powerball-tickets-sold-this-time-will-duplicates/ZIn5u0Cm2KgGZnwWSZ4UBO/story.html More than half of Powerball tickets sold this time will be duplicates]<br>
by Matt Rocheleau, ''Boston Globe'', 13 January 2016.
 
This article appeared on the morning of the drawing.  It noted that of the 440 million tickets had been sold the previous Saturday.  This is more than enough to cover every possible number combination


==Some math doodles==
==Some math doodles==
<math>P \left({A_1 \cup A_2}\right) = P\left({A_1}\right) + P\left({A_2}\right) -P \left({A_1 \cap A_2}\right)</math>
<math>P \left({A_1 \cup A_2}\right) = P\left({A_1}\right) + P\left({A_2}\right) -P \left({A_1 \cap A_2}\right)</math>
<math>P(E)  = {n \choose k} p^k (1-p)^{ n-k}</math>


<math>\hat{p}(H|H)</math>
<math>\hat{p}(H|H)</math>


<math>\hat{p}(H|HH)</math>
<math>\hat{p}(H|HH)</math>

Latest revision as of 20:58, 17 July 2019


Forsooth

Quotations

“We know that people tend to overestimate the frequency of well-publicized, spectacular events compared with more commonplace ones; this is a well-understood phenomenon in the literature of risk assessment and leads to the truism that when statistics plays folklore, folklore always wins in a rout.”

-- Donald Kennedy (former president of Stanford University), Academic Duty, Harvard University Press, 1997, p.17

"Using scientific language and measurement doesn’t prevent a researcher from conducting flawed experiments and drawing wrong conclusions — especially when they confirm preconceptions."

-- Blaise Agüera y Arcas, Margaret Mitchell and Alexander Todoorov, quoted in: The racist history behind facial recognition, New York Times, 10 July 2019

In progress

What if the Placebo Effect Isn’t a Trick?
by Gary Greenberg, New York Times Magazine, 7 November 2018

The Problems With Risk Assessment Tools
by Chelsea Barabas, Karthik Dinakar and Colin Doyle, New York Times, 17 July 2019

Hurricane Maria deaths

Laura Kapitula sent the following to the Isolated Statisticians e-mail list:

[Why counting casualties after a hurricane is so hard]
by Jo Craven McGinty, Wall Street Journal, 7 September 2018

The article is subtitled: Indirect deaths—such as those caused by gaps in medication—can occur months after a storm, complicating tallies

Laura noted that

Did 4,645 people die in Hurricane Maria? Nope.
by Glenn Kessler, Washington Post, 1 June 2018

The source of the 4645 figure is a NEJM article. Point estimate, the 95% confidence interval ran from 793 to 8498.

President Trump has asserted that the actual number is 6 to 18. The Post article notes that Puerto Rican official had asked researchers at George Washington University to do an estimate of the death toll. That work is not complete. George Washington University study

We sttill don’t know how many people died because of Katrina
by Carl Bialik, FiveThirtyEight, 26 August 2015

These 3 Hurricane Misconceptions Can Be Dangerous. Scientists Want to Clear Them Up.
Misinterpretations of the “Cone of Uncertainty” in Florida during the 2004 Hurricane Season
Definition of the NHC Track Forecast Cone


Remember when a glass of wine a day was good for you? Here's why that changed. Popular Science, 10 September 2018


Googling the news
Economist, 1 September 2018

We sat in on an internal Google meeting where they talked about changing the search algorithm — here's what we learned


Reading , Writing and Risk Literacy

[1]


Today is the deadliest day of the year for car wrecks in the U.S.

Some math doodles

<math>P \left({A_1 \cup A_2}\right) = P\left({A_1}\right) + P\left({A_2}\right) -P \left({A_1 \cap A_2}\right)</math>

<math>P(E) = {n \choose k} p^k (1-p)^{ n-k}</math>

<math>\hat{p}(H|H)</math>

<math>\hat{p}(H|HH)</math>

Accidental insights

My collective understanding of Power Laws would fit beneath the shallow end of the long tail. Curiosity, however, easily fills the fat end. I long have been intrigued by the concept and the surprisingly common appearance of power laws in varied natural, social and organizational dynamics. But, am I just seeing a statistical novelty or is there meaning and utility in Power Law relationships? Here’s a case in point.

While carrying a pair of 10 lb. hand weights one, by chance, slipped from my grasp and fell onto a piece of ceramic tile I had left on the carpeted floor. The fractured tile was inconsequential, meant for the trash.

BrokenTile.jpg

As I stared, slightly annoyed, at the mess, a favorite maxim of the Greek philosopher, Epictetus, came to mind: “On the occasion of every accident that befalls you, turn to yourself and ask what power you have to put it to use.” Could this array of large and small polygons form a Power Law? With curiosity piqued, I collected all the fragments and measured the area of each piece.

Piece Sq. Inches % of Total
1 43.25 31.9%
2 35.25 26.0%
3 23.25 17.2%
4 14.10 10.4%
5 7.10 5.2%
6 4.70 3.5%
7 3.60 2.7%
8 3.03 2.2%
9 0.66 0.5%
10 0.61 0.5%
Montante plot1.png

The data and plot look like a Power Law distribution. The first plot is an exponential fit of percent total area. The second plot is same data on a log normal format. Clue: Ok, data fits a straight line. I found myself again in the shallow end of the knowledge curve. Does the data reflect a Power Law or something else, and if it does what does it reflect? What insights can I gain from this accident? Favorite maxims of Epictetus and Pasteur echoed in my head: “On the occasion of every accident that befalls you, remember to turn to yourself and inquire what power you have to turn it to use” and “Chance favors only the prepared mind.”

Montante plot2.png

My “prepared” mind searched for answers, leading me down varied learning paths. Tapping the power of networks, I dropped a note to Chance News editor Bill Peterson. His quick web search surfaced a story from Nature News on research by Hans Herrmann, et. al. Shattered eggs reveal secrets of explosions. As described there, researchers have found power-law relationships for the fragments produced by shattering a pane of glass or breaking a solid object, such as a stone. Seems there is a science underpinning how things break and explode; potentially useful in Forensic reconstructions. Bill also provided a link to a vignette from CRAN describing a maximum likelihood procedure for fitting a Power Law relationship. I am now learning my way through that.

Submitted by William Montante